Long Range People Detection User Guide

Table of Contents

Overview

This lab demonstrates the use of TI mmWave sensors to count and track multiple people simultaneously up to 100m away.

Beamforming and Beamsteering have been implemented on the device for the 6843 version in order to increase the detection range for a person past 100 meters. Every 400 ms, the device completes a scan across a 90 degree field of view, generating tracks for people, vehicles, and other moving objects. Static objects, such as trees, signs, and buildings are ignored. This lab also supports the 50 meter chirp configurations, which provide a 20 Hz update rate (instead of 2.5 Hz with Beamsteering), leading to smoother tracker performance.

Performance Expectation

The lab comes with a few default chirps

You can see a performance comparison in the charts below. The 2D and 3D 50 meter chirps will have very similar performance, but the 2D chirp has more chirps per virual reciever, which allows it to detect longer range values, as shown below. The Tx Beamforming chirp uses all 3 Tx in each chirp, so it is limited to 2D. Unlike the 50 meter chirps, the beamforming chirp has much more consistent range across its FOV as the radiation pattern is directed in each direction during the duration of the chirp.

Additionally, you can see that the performance on 6443 is slightly worse than on 6843 when using TX beamforming due to hardware limitations.

Angle of Arrival (degrees) 2D Approaching (m) 3D Approaching (m) 2D Departing (m) 3D Departing (m) 6443 Tx Beamforming Approaching 6443 Tx Beamforming Departing 6843 Tx Beamforming Approaching 6843 Tx Beamforming Departing
0 56 56 56 56 >100 >100 >100 >100
15 55 55 55 56 >80 >80 >100 >100
30 55 44 55 50 >80 >80 >100 >100
45 56 42 55 42 >80 >80 >100 >100
60 34 28 45 34 NA NA NA NA

Tuning compRangeBiasAndRxChanPhase

compRangeBiasAndRxChanPhase is a parameter in the cfg file that lets users account for near field effects between antennas. Tuning compRangeBiasAndRxChanPhase will improve the device’s angle estimation. compRangeBiasAndRxChanPhase should always be tuned for devices in production, but in development, some customers choose to not tune this parameter.

In the Long Range People Detection Lab though, since the expectation is that targets are a long distance away, small errors in azimuth angle estimation result in larger errors in the X-position of objects. Therefore, TI recommends customers tune this parameter individually for every board used during development. The procedure for tuning this parameter can be found in the SDK User’s Guide.

How Beamforming and Beamsteering Work

Normally, the device is run in TDM-MIMO mode, meaning that only one transmitter chirps at a time, and all the recievers listen for the return signal. In TDM-MIMO, a frame is made up of each transmitter chirping multiple times. When beamforming is implemented though, all the recievers are still listening to each chirp. However, all of the transmitters chirp in unison. The transmitted signals constructively and destructively interfere with each other. Constructive interference occurs in the area directly in front of the radar, in the shape of a cone with a 22.5 degree angle to boresight. Destructive interference occurs in the rest of the field of view, outside this cone. The area inside the 22.5 degree cone of constructive interference has much stronger signal strength, leading to longer range detection. Beamsteering is the process of directing this cone in various directions by manipulating the phase offset of each transmitter. This changes where the constructive and destructive interference happen, leaving the beam pointed in a different direction.

In the Long Range People Detection demo, four subframes are configured, each one steering the beam in a different direction. These are configured in such way that the beams cumulatively cover the area from -45 degrees to + 45 degrees. For each subframe, the point cloud is generated, then stored. After all four subframes have completed, the point clouds are merged and sent to the tracker. After this process, all of the point cloud and tracking data is output from the device. Each complete scan takes 400 ms.

Please see the document Beamforming_in_LRPD.pdf to understand how to set the phase offset values to change the beam direction. Also included are two scripts, (phaseShift.py and phaseShift.m) to calculate the beamsteer offset given a intended angle. Reading the Beamforming_in_LRPD.pdf document is recommended before using the scripts.

Using the Scripts to Calculate Phase Offset Value

phaseShift.py

  1. Modify line 3 to have the angles you want to focus the beam at. Default is [-20, 0, 20] - with this input, the script will output 3 phase shift values.
  2. Run the script, note the phase shift values. These values are in the same order as the thetas.
  3. Replace the phase shift values in the profileCfg lines in the chirp configuration file with the output values. There needs to be 1 profileCfg for each output value.

phaseShift.m

  1. Modify line 1 to be the angle you want to see output for. This script does one angle value at a time.
  2. Run the script
  3. The output will be a phase shift value which must be placed inside the profileCfg argument inside the chirp config file.
  4. Repeat steps 1 through 3 for each beam.

Quickstart

1. Hardware and Software Requirements

⚠️ MMWAVEICBOOST Required

The beamforming/beamsteering feature described earlier requires the ICBOOST board to facilitate higher power draw required to use this feature. Using the ISK board standalone will result in poor RF performance. This usually manifests as a noisy point cloud.

Hardware

Item Details
IWR6843ISK IWR6843 Long Range Antenna Board
Carrier Board mmWave Carrier Board (Only needed if using beamforming configurations)
Mounting Hardware The EVM needs to be mounted at a height of ~2.0-2.5m with a slight downtilt
Micro USB Cable Due to the high mounting height of the EVM, an 8ft+ cable or USB extension cable is recommended
Power Supply 5V, 3A with 2.1-mm barrel jack (center positive). The power supply can be wall adapter style or a battery pack with a USB to barrel jack cable. Only needed if using an MMWAVEICBOOST

Software

Tool Version Required For Download Link
Uniflash Latest Flashing Firmware Download offline tool or use cloud version

2. Flash the EVM

  1. Follow the instructions for Hardware Setup of ICB for Flashing Mode
  2. Find the prebuilt binary for your devicefrom the prebuilt_binaries folder contained in this lab
  3. Flash this prebuilt binary onto your device by following the instruction to Flash the mmWave Device

3. Physical Setup

  1. Follow the instructions for Hardware Setup of ISK for Functional Mode
  2. For best results, the EVM should be positioned high enough to be above the top of tracked objects and with a slight down tilt. The aim is to position the EVM so that the antenna beam can encompass the area of interest. If the down tilt is too severe, noise from ground clutter would increase and the effective sensing area would decrease. If threre is no down tilt, counting performance would be worse for cases in which one person is in line with and shielded by another person. Given the antenna radiation pattern of the EVM, consideration should be taken to not mount the EVM too close or oriented with beam directed to the ceiling as this can increase the noise floor and result in less optimal performance.

Setup Requirements:

Setup using suggested tripod and smartphone clamp mount:

  1. Screw on clamp mount to tripod
  2. Clamp EVM across its width below power barrel jack to attach EVM
  3. Adjust tripod head for ~2-3 degree down tilt (Tip: Bubble or level smartphone apps can be used to measure down tilt)
  4. Plug in micro-usb and power supply to EVM
  5. Extend tripod so that the EVM is elevated 2.0-2.5m from the ground
  6. Position EVM and tripod assembly in desired location of room. The EVM should be positioned so that the 120 degree FOV of the EVM antenna encompasses the area of interest and points to the region in which people are expected to enter the space.

4. Run the Lab

To run the lab, launch and configure the visualizer which displays the detection and tracked object data received via UART. The visualizer is found at <Toolbox Install Dir>\tools\visualizers\Industrial_Visualizer

Ensure that cfg file selected is from the chirp_configs folder contained in this lab.

Developer’s Guide

Build the Firmware from Source Code

1. Software Requirements

Tool Version Download Link
TI mmWave SDK 3.5.x.x TI mmWave SDK and all the related tools are required to be installed as specified in the mmWave SDK release notes
Code Composer Studio Latest Code Composer Studio
Uniflash Latest Uniflash tool is used for flashing TI mmWave Radar devices. Download offline tool or use the Cloud version

2. Import Lab Project

For the 6843 lab, there are two projects, the DSS for the C674x DSP core and the MSS project for the R4F core, that need to be imported to CCS and compiled to generate firmware for the xWR6843. The 6443 version of this lab will only contain the MSS project for the R4F core.

⚠️ WARNING
When importing projects to a workspace, a copy is created in the workspace. All modifications will only be implemented for the workspace copy. The original project downloaded from the Toolbox is not touched.

  1. Start CCS and setup workspace as desired.
  2. Import the project(s) specified below to CCS. See instructions for importing here.
    • long_range_people_det_6843_mss and long_range_people_det_6843_dss
    • long_range_people_det_6443_mss
  3. Verify that the import occurred without error: in CCS Project Explorer, the projects should appear.

3. Build the Lab

The DSS project must be built before the MSS project if using the 6843.

  1. Select the long_range_people_det_dss so it is highlighted. Right click on the project and select Rebuild Project. The DSS project will build.
  2. Select the long_range_people_det_mss so it is highlighted. Right click on the project and select Rebuild Project. The MSS project will build, the the lab binary will be constructed automatically.
  3. On successful build, the following should appear:
    • In long_range_people_det_dss → Debug, long_range_people_det_dss.xe674 (this is the C67x binary used for CCS debug mode)
    • In long_range_people_det_mss → Debug, long_range_people_det_mss.xer4f (this is the Cortex R4F binary used for CCS debug mode) and long_range_people_det_lab.bin (this is the flashable binary used for deployment mode)

⚠️ WARNING - Selecting Rebuild
Selecting Rebuild instead of Build ensures that the project is always re-compiled. This is especially important in case the previous build failed with errors.}}

⚠️ WARNING - Build Fails with Errors
If the build fails with errors, please ensure that all the software requirements are installed as listed above and in the mmWave SDK release notes.

📝 NOTE - Existing Binaries
As mentioned in the Quickstart section, pre-built binary files, both debug and deployment binaries are provided in the pre-compiled directory of the lab.

4. Execute the Lab

There are two ways to execute the compiled code on the EVM:

After executing the lab using either method, the lab can be visualized using the executable in the <Toolbox Install Dir>\tools\visualizers\Industrial_Visualizer folder or continue to working with the GUI Source Code

Data Formats

A TLV(type-length-value) encoding scheme is used with little endian byte order. For every frame, a packet is sent consisting of a fixed sized Frame Header and then a variable number of TLVs depending on what was detected in that scene. The TLVs can be of types representing the point cloud, target list object, and associated points.

Frame Header

Length: 40 Bytes

A Frame Header is sent at the start of each packet. Use the Magic Word to find the start of each packet.

Value Type Bytes Comments
Magic Word uint64_t 8 syncPattern in hex is: ‘02 01 04 03 06 05 08 07’
Version unint32_t 4 Software Version
Total Packet Length unint32_t 4 In bytes, including header
Platform unint32_t 4 A6843
Frame Number unint32_t 4 Frame Number
Time [in CPU Cycles] unint32_t 4 Message create time in cycles
Num Detected Obj unint32_t 4 Number of detected points in this frame
Num TLVs unint32_t 4 Number of TLVs in this frame
Subframe Number unint32_t 4 Sub-Frame number

TLV Header

Length: 8 Bytes

A TLV Header is sent at the start of each TLV. Following the header, is the the TLV-type specific payload. The TLVs can be of type
MMWDEMO_OUTPUT_MSG_SPHERICAL_POINTS, MMWDEMO_OUTPUT_MSG_DETECTED_POINTS_SIDE_INFO, MMWDEMO_OUTPUT_MSG_TRACKERPROC_3D_TARGET_LIST, or MMWDEMO_OUTPUT_MSG_TRACKERPROC_TARGET_INDEX.

Value Type Bytes Comments
Type unint32_t 4 TLV Type: 06 = DPIF Point cloud spherical,
07 = Target object list, 08 = Target index, 09 = DPIF Point Cloud Side Info
Length [number of bytes] unint32_t 4 In bytes

TLVs

Point Cloud TLV

Size: sizeof (DPIF_PointCloudSpherical) x numberOfPoints

Each Point Cloud TLV consists of an array of points. Each point is defined in 16 bytes.

Value Type Bytes Comments
range float 4 Range, in meters
azimuth float 4 Azimuth, in radians
elevation float 4 Elevation in radians
doppler float 4 Doppler, in m/s

Point Cloud Side Info TLV

Type: MMWDEMO_OUTPUT_MSG_DETECTED_POINTS_SIDE_INFO

Size: sizeof(DPIF_PointCloudSideInfo) x numberOfPoints

Each Point Cloud Side Info TLV consists of an array of point side info data. Each is 8 bytes.

Value Type Bytes Comments
SNR int16_t 2 SNR, ratio
Noise int16_t 2

Target List TLV

Size: sizeof (tlvHeaderStruct) + sizeof (trackerProc_Target) x numberOfTargets The Target List TLV consists of an array of targets. Each target object is defined as given below.

Value Type Bytes Comments
tid uint32 4 Track ID
posX float 4 Target position in X dimension, meters
posY float 4 Target position in Y dimension, meters
posZ float 4 Target position in Z dimension, meters
velX float 4 Target velocity in X dimension, meters/s
velY float 4 Target velocity in Y dimension, meters/s
velZ float 4 Target velocity in Z dimension, meters/s
accX float 4 Target acceleration in X dimension, meters/s2
accY float 4 Target acceleration in Y dimension, meters/s
accZ float 4 Target acceleration in Z dimension, meters/s
ec[16] float 16x4 Tracking error covariance matrix, [4x4] in range/azimuth/elevation/doppler coordinates
g float 4 Gating function gain
confidenceLevel float 4 Confidence Level

Target Index TLV

Size: sizeof (tlvHeaderStruct) + sizeof(uint8) x numberOfPoints (NOTE: here the number of points are for frame n-1)

The Target Index TLV consists of an array of target IDs. A targetID at index i is the target to which point i of the previous frame’s point cloud was associated. Valid IDs range from 0-249.

Value Type Bytes Comments
targetID uint8_t 1 Track ID

Other Target ID values:

Value Meaning
253 Point not associated, SNR too weak
254 Point not associated, located outside boundary of interest
255 Point not associated, considered as noise

Customization

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